Modern businesses create, collect, analyze, and store vast amounts of data on metrics that impact their operations and decision-making. The amount is forecasted to grow to even more monumental proportions in the near future. With data workflows becoming more critical than ever, many organizational leaders are beginning to recognize just how important it is to achieve data observability. As enterprises actively pursue data management initiatives, it’s clear that observability is essential in achieving business growth. This article will detail what data observability is, and how businesses can take advantage of it to increase their bottom line.
What is data observability?
Data observability refers to an organization’s ability to have full oversight of the health of its data and the processes that affect data health. With it, organizations gain insight into their entire data pipeline and can optimize data processes and evaluate their performance. As data becomes more integral to business continuity and efficient operations, it’s crucial for businesses to incorporate it into their data management strategy.
Organizations with full data oversight can quickly identify and resolve inefficiencies, potential points of failure, and other issues that could affect their operations.
By conducting constant and automated monitoring to highlight data issues in a timely manner for immediate and effective resolution, data observability goes far beyond the benefits of regular data analysis. Without it, organizations are limited to viewing their data as a snapshot in time rather than seeing a real-time view of their operations.
8 ways data observability positively affects your bottom line
1. Transforms unstructured data into insight
With organizations generating staggering amounts of data daily, converting it into useful insights can inform better business decisions and improve customer engagement. This can help companies achieve a holistic view of their organization and its data processes by providing more than just a rudimentary understanding of operational data. To generate insights that boost growth, cloud data platforms like Panoply build a single source of truth to clear the path for revenue growth. With little coding needed to connect all of your data sources, Panoply allows you to access high-level data analysis to support improved decision making.
2. Reduces downtime
As organizations become increasingly reliant on data to conduct their operations, unresolved data issues can lead to unexpected downtime. In turn, this can harm a brand’s reputation and productivity, causing monetary losses. However, data observability tools allow businesses to address problems quickly to protect operations from being impacted further, thus reducing downtime.
3. Increases productivity
Many businesses rely on their data to discover new insights about how they can maximize their output with limited resources. Oversight can help organizations discover workflows and automations that can save administrative professionals and operational teams thousands of hours each year. Data observability spearheads optimization efforts, providing a complete picture of company assets and highlighting how each can be used to maximize value and increase the bottom line.
4. Provides a single source of truth
With a single source of truth (SSOT), a unified source of data informs company decisions much better than relying on data from disparate sources. Organizations that use a robust data and business intelligence infrastructure that runs on an SSOT can avoid duplicate data entries and reduce the amount of time spent determining which data is correct. As a result, businesses are in a better position to increase their bottom line. By storing data from all sources in a cloud data warehouse, Panoply creates that single source of truth and provides a 360-degree view of your business to guarantee visibility into the right data.
5. Helps identify more opportunities
In rapidly-evolving marketplaces, full data oversight is instrumental in identifying new, and better, opportunities to drive profits. It can help businesses establish strong relationships with customers and provide deep insights into industry developments. Companies can pair internal data with publicly available industry data for an accurate overview of both opportunities and challenges within their environment. With data observability providing routine analysis of this information, business leaders can react to opportunities quickly to get a step ahead of competitors.
6. Improves efficiency
A major benefit of data observability is that it delivers real-time data, enabling organizations with data-centric workloads to be more efficient. With an accurate view of how data processes help a business achieve its goals, operational teams can use the data to inform their sales outreach, financial forecasting, marketing strategies, and much more. Because data observability guarantees fast and accurate data processes, businesses can collect the critical information they need faster. This often leads to increased revenue, and as a result, a growing bottom line.
7. Timely rectification of data issues
If left unattended, data issues can be extremely disruptive and cause financial setbacks. Problems like inaccuracies or inconsistencies can negatively impact productivity levels, and in some circumstances can even compromise a company’s reputation. Therefore, it’s critical to identify and resolve data issues quickly, before they become an existential challenge instead of an easy-to-fix operational snag. With solid data observability, processes are simplified so data remains safe, accessible, and reliable at all times. When processes can be automated and problems quickly rectified, every part of a business — including a company’s bottom line — benefits from it.
8. Augmented performance
One of the reasons organizations implement widespread data collection and analysis is to ensure that their business is consistently performing at optimal levels. Because data observability provides clear operational data, it can help users discover inefficiencies. By analyzing such data, teams are also able to determine the right course of action to enable higher levels of performance and output. When performance is augmented, so is your bottom line. Simplifying and automating data tasks at scale empowers faster innovation. Acceldata makes doing so achievable, and also protects organizations from costly refactoring by optimizing solutions for performance, quality, and cost.
Achieving data observability at your organization
Data observability can help organizations do so much more than simply collect and store operational and administrative information. Businesses that build and maintain a holistic view of their data, data health, and data processes are significantly more likely to improve their bottom line.
As data tools continue to emerge on the market, data observability has never been more achievable for businesses of any industry. However, success requires effort, and companies must take a holistic and proactive approach to data management. With the right tools and techniques, companies can not only improve data quality and make better decisions while increasing their efficiency, they can benefit from a better bottom line as well.
Loretta Jones is VP growth at Acceldata.io with extensive experience marketing to SMBs, mid-market companies, and enterprise organizations. She is a self-proclaimed 'startup junkie’ and enjoys growing early-stage startups. She studied Psychology at Brown University and credits this major to successful marketing as well as navigating a career in Silicon Valley. She’s a nature lover and typically schedules her vacations around the migratory patterns of whales and large ocean creatures.